Screening the low molecular weight fraction of human serum using ATR-IR spectroscopy

J Biophotonics. 2016 Oct;9(10):1085-1097. doi: 10.1002/jbio.201600015. Epub 2016 Aug 10.

Abstract

Vibrational spectroscopic techniques can detect small variations in molecular content, linked with disease, showing promise for screening and early diagnosis. Biological fluids, particularly blood serum, are potentially valuable for diagnosis purposes. The so-called Low Molecular Weight Fraction (LMWF) contains the associated peptidome and metabolome and has been identified as potentially the most relevant molecular population for disease-associated biomarker research. Although vibrational spectroscopy can deliver a specific chemical fingerprint of the samples, the High Molecular Weight Fraction (HMWF), composed of the most abundant serum proteins, strongly dominates the response and ultimately makes the detection of minor spectral variations a challenging task. Spectroscopic detection of potential serum biomarkers present at relatively low concentrations can be improved using pre-analytical depletion of the HMWF. In the present study, human serum fractionation by centrifugal filtration was used prior to analysis by Attenuated Total Reflection infrared spectroscopy. Using a model sample based on glycine spiked serum, it is demonstrated that the screening of the LMWF can be applied to quantify blinded concentrations up to 50 times lower. Moreover, the approach is easily transferable to different bodily fluids which would support the development of more efficient and suitable clinical protocols exploring vibrational spectroscopy based ex-vivo diagnostic tools. Revealing serum LMWF for spectral serological diagnostic applications.

Keywords: Attenuated Total Reflection (ATR); IR spectroscopy; Low Molecular Weight Fraction (LMWF); Principal Component Analysis; centrifugal filtration; human serum.

MeSH terms

  • Biomarkers / blood
  • Humans
  • Molecular Weight
  • Serum / chemistry*
  • Spectrophotometry, Infrared*

Substances

  • Biomarkers